• Journal of Construction Engineering and Project Management
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• 제7권3호
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• pp.39-55
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• 2017

Preeminent performance of construction industry are unattainable with poor productivity resulting in time and cost over runs. Enhancement in productivity cannot be achieved without identifying and analyzing factors that adversely affect productivity. The objective therefore is to propose a productivity analysis model to quantify the probability of effect of factors influencing productivity by using fuzzy logic incorporated with relative importance index method, for various types of construction projects. To achieve this objective, a questionnaire survey was carried out targeting respondents of Indian construction industry, from four distinct projects, namely, residential, commercial, infrastructure and industrial projects. Based on questionnaire administered, the relative importance and ranks of factors demonstrated using relative importance index method. Probability assessment model to analyze productivity was then developed by using Fuzzy Logic Toolbox of MATLAB. The applicability of the proposed model was tested in seven construction projects and the probability of impact of factors on productivity evaluated. The results of application of model in the construction firms infers that the most contributing factor groups for most of the projects were discerned to be manpower, motivation and time group.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2009년도 춘계학술대회 논문집
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• pp.378-381
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• 2009

This paper investigates the productivity growth in Korean railway transport. The productivity growth is calculated by a process of measuring of pure efficiency change index(PECI), scale efficiency change index(SECI), and technical change index(TCI), using Data envelopment analysis (DEA) method. The data cover the period 1999$\sim$2006; 1999$\sim$2003 are the pre-structural reform years and the post-structural reform years are 2004$\sim$2006. The framework for the analysis is Malmquist Productivity Index (MPI) of the to investigate the impacts of structural reform on productivity growth, respectively. The inputs considered are the length of operating line, the number of staff, the number of coach and wagon, and the outputs are the trains movement of passenger and freight, and the traffic of passenger and freight. Results indicate that Korean railway experienced a annual productivity growth of approx. 3% after the structural reform.

• 보건의료산업학회지
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• 제10권2호
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• pp.15-23
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• 2016

Objectives : The purpose of this study was to evaluate the productivity changes of 18 public health centers in Gangwon-do from 2006 to 2013 using the Malmquist Productivity Index(MPI). Methods : Data were collected from Statistics Korea from 2006 to 2013. The input variables were the numbers of medical, nursing and administrative personnels. The output variables were the performances of health promotion programs. Along with the traditional input-oriented DEA analysis, the MPI was calculated. Results : First, among the 18 public health centers, the productivity index of 14 public health centers was increased. Second, the annual productivity showed a 6% increase. Third, the productivity improvements were mainly caused by Scale Efficiency Change. Conclusions : Improving the productivity of public health centers requires the support and external policies of the national and local government. Internally, public health centers need to maintain scale optimization of the center. Additionally, efforts should be made to effectively use limited resources.

• Ocean and Polar Research
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• 제32권4호
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• pp.387-396
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• 2010

This paper estimates changes in the total factor productivity and technical efficiency change index and the technical change index using the Malmquist productivity index (MPI) in fishery-processed wholesale products over the time period spanning 2006-2008. The model considers a number of employees and operating costs as input factors, and sales and EBIT (earnings before tax and interest) as output factors. The results demonstrate that, between 2006 and 2007, there has generally been no technical progress, although a small improvement in productivity was detected in the sales scale of 10 billion won-50 billion won. Between 2007 and 2008, there was technical progress in the majority of DMU, except within the range of 20 million won-10 billion won. Wilcoxon's rank-sum test, however, demonstrates no statistically significant differences in productivity between the two periods.

• 한국항해항만학회지
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• 제44권5호
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• pp.400-406
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• 2020

In this study, we first measured the malmquist productivity index by DEA among the Korean public firms. Second, there are 12 public corporations whose productivity (MPI) has decreased compared to 2014. This is mainly because of a decrease in productivity, as well as a decrease in the technical efficiency change index (TECI), impacted by the internal environment, and the increase in productivity because of an increase in the technology change index (TCI) impacted by the external environment. Finally, the analysis of the impact on the management assessment scores showed that the productivity (MPI), scale efficiency (CRS), size of sales, operating profitability, and total capital investment efficiency are significantly related (+), except for the asset turnover, which is a static financial ratio. Meanwhile, the management evaluation scores between the high-productivity public corporations and low-performing public corporations were significantly discriminating. Thus, it is confirmed that the nation's state-run companies must manage their MPIs in a time series to score high in management evaluation.

• 대한안전경영과학회지
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• 제19권1호
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• pp.219-226
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• 2017

This study investigates application cases of facility management system model for enhancing facility productivity of industry filed around medium and small facility processing companies and finds the inefficiency of the existing management model. Following items are researched to seek out methods and measures to maximize facility productivity through empirical analysis by exploring and establishing a new management model. First, the empirical analysis, it is found that the overall equipment efficiency index used for facility productivity management in the companies has a difficulty being used as the index for it in actual medium-small processing companies. Second, a new facility management system model applying standard cycle time is suggested among facility management index system to measure facility productivity. Third, the empirical analysis is used to verify that developed facility management system model is a useful method to manage the facility productivity by applying the model to actual medium-small processing companies. Finally, it is necessary to implement comparison analysis on whether actual productivity enhancement induces a distinctly different result by using a new facility management index system model to be inhibited in this study.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2010년도 춘계학술대회 논문집
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• pp.432-436
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• 2010

This paper investigates the productivity growth in Korean railway lines. The productivity growth is calculated by a process of measuring of pure efficiency change index(PECI), scale efficiency change index(SECI), and technical change index(TCI), using Data envelopment analysis (DEA) method. The data cover the period 1990~2007; 1990~2003 are the pre-structural reform years and the post-structural reform years are 2005~2007. The framework for the analysis is Malmquist Productivity Index (MPI) of the to investigate the impacts of structural reform on productivity growth, respectively. The inputs considered are the length of operating line, the number of staff, the number of coach and wagon, and the outputs are the trains movement of passenger and freight, and the traffic of passenger and freight.

• Spatial Information Research
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• 제9권2호
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• pp.341-352
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• 2001

이 연구는 지리정보시스템(GIS)로 구한 토지생산성지수(FPI)와 노동생산성지수(LPI)를 적용하여 농지의 잠재생산성지수(PPI)를 산정할 수 있는 모형을 개발하였고, 최근 경지정리사업이 완료된 지구에 적용하여 개발된 모형의 적용성을 검토하였다. 토지 생산성지수(FPI)는 분석대상지역의 토양 특성 Poly Grid를 중첩하여 결정하였으며, 노동생산성 지수(LPI)는 직접생산비중 GIS Network 분석으로 구한 통작거리와 논지분포에 따른 노력비 추가분을 전체 직접생산비에 대하 비율로 환산하였다. 마수지구와 원천지구의 개별 농지에 대한 전체생산성지수(PPI)는 각각 0.967∼0.712, 0.986∼0.780으로 비교적 큰 변이를 나타낼 수 있어 농지 평가에 대한 객관적인 자료로 적용할 수 있을 것이다. 농지의 잠재생산성지수를 경지정리 사업의 환지사업, 농민상호간에 농지교환 및 합병사업에 적용함으로써 농지의 규모화 및 집단화을 유도하고 농지생산성을 극대화할 수 있을 것이다.

• 품질경영학회지
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• 제38권2호
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• pp.261-275
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• 2010

The purpose of this study is to empirically analyze the productivity change of the 10 Single PPM Certification Company in the 3 Industry(Electronics, Motor-Parts, Machines). In this study, Productivity change over the time in Korean small and medium sized firms in the 3 industries by the bootstrapped Malmquist Productivity Index(MPI). The traditional Malmquist Productivity Index(MPI) and Data Envelopment Analysis(DEA) Models have not only bias but also lack statistical confidence intervals. they could lead to wrong evaluations of the efficiency and productivity scores. In this paper, DEA and a MPI are combined with a bootstrap method in order to provide statistical inferences that analyze the performance of the Single PPM Certification Company. The data cover the period between 2004 and 2007. The result of this paper reveals : 1) The Electronics Industry had productivity effect of 17%, but there was not direct effect for other Industries(Motor-Parts, Machines). 2) average productivity Progress of the 7DMU(Electronics), 1DMU(Motor-Parts) and none(Machines).

• 농업과학연구
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• 제45권4호
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• pp.871-878
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• 2018

The government of Gyeongbuk in Korea increased the financial input in the agricultural sector by 43% from 2008 through 2012. However, the productivity of the agricultural sector in Gyeongbuk rose only about 3.6% during the same period. This study evaluated the agricultural competitiveness of each city or county in Gyeongbuk using six evaluation indices (scale, productivity, finance input, location quotient, technical education, and total) and investigated the relationship between the indices and total values of agricultural productions. The results show that Sangju, Gyeongju, Andong, Uiseong, and Seongju have high competitiveness for the scale index. For the productivity index, Gimcheon, Mungyeong, Ulleung, Yeongju, and Seongju were highly evaluated. For the location quotient index, Yeongcheon, Uiseong, Cheongdo, Seongju, and Sangju have high competitiveness. Uiseong, Yeongdeok, Cheongsong, Gunwi, and Yeongyang were highly evaluated for the agricultural finance input index. For the agricultural technical education index, Chilgok, Sangju, Mungyeong, Uiseong, and Gyeongju have high competitiveness. Finally, Sangju, Euiseong, Yeongcheon, Gyeongju, and Andong were highly evaluated for the total competitive index, while Yeongdeok, Yeongyang, Goryeong, Uljin, and Cheongsong have a low competitiveness for the total competitive index. This study also found that out of five indices, scale, location quotient, and technical education indices have a positive and statistically significant effect on the total values of agricultural production. However, we did not find any statistically significant effect of the productivity and finance input indices on the total values of agricultural production. Hence, we can conclude that the government should focus their agricultural policy on scale, location quotient and education to improve total agricultural production.